{"id":"W6931450309","doi":"10.5281/zenodo.5894506","title":"Replication package for: \"Slow Recoveries and Unemployment Traps: Monetary Policy in a Time of Hysteresis\"","year":2022,"lang":"en","type":"other","venue":"Zenodo (CERN European Organization for Nuclear Research)","topic":"Ophthalmology and Visual Impairment Studies","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Bank of Canada","funders":"","keywords":"Unemployment; Replication (statistics); Monetary policy; Full employment","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":["metaresearch","open_science","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.008358913,0.002441457,0.002370137,0.002574509,0.002032245,0.002716162,0.003290481,0.002458048,0.7007699],"category_scores_gemma":[0.09191152,0.001653693,0.00378387,0.004389872,0.0006386967,0.00208206,0.002585704,0.002853706,0.2704907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001135007,"about_ca_system_score_gemma":0.005320957,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01090221,"about_ca_topic_score_gemma":0.0102388,"domain_scores_codex":[0.9959511,0.001610878,0.0005617212,0.0007089244,0.0008012224,0.0003662384],"domain_scores_gemma":[0.9563584,0.01890546,0.001439835,0.01341016,0.00862675,0.001259336],"domain_codex":null,"domain_gemma":"reproducibility","domain_candidate":"reproducibility","domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006288589,0.00008158509,0.0004805579,0.001026684,0.0001091239,0.00004345889,0.0001215945,0.0006776048,0.0002451215,0.002336198,0.9817553,0.01249398],"study_design_scores_gemma":[0.006706826,0.0003320267,0.007901712,0.001818521,0.0004481204,0.000195994,0.000318466,0.004392087,0.001910886,0.02699611,0.9486634,0.0003159639],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0009511397,0.00009315841,0.01862847,0.001132143,0.002042708,0.002751458,0.9492645,0.01211253,0.01302384],"genre_scores_gemma":[0.02317142,0.0004958906,0.081016,0.001688352,0.001136967,0.04838329,0.7583865,0.02638476,0.05933679],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9967095,"threshold_uncertainty_score":0.4268154,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04100208479797841,"score_gpt":0.3138742861895147,"score_spread":0.2728722013915363,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}